The subject matter disclosed herein relates generally to systems and methods for computed tomography (CT) imaging, and for filtering of data acquired by or associated with CT imaging.
In CT imaging, an X-ray source may be rotated around an object to obtain imaging information. X-rays from the source attenuated by the object may be collected or detected by a detector and used to reconstruct an image. As part of image reconstruction, multi-material correction (MMC) may be performed. MMC helps address, for example, the heel effect (e.g., improving houndsfield unit (HU) uniformity across Z-coverage), as well as other issues affecting accurate image reconstruction.
Ideally, for high quality correction performance, during the implementation of a MMC algorithm, the reconstruction displayed field of view (DFOV) should be relatively large, for example, about 70 centimeters. Accordingly, the reconstruction size (or pixel matrix) may need to be increased to maintain a same or even higher pixel resolution as a final reconstruction image. However, practical difficulties are encountered in increasing pixel matrix size, for example due to practical restrictions or limitations on memory and/or computational time. For example, in certain conventional systems, to accelerate reconstruction speed, a pixel matrix of about 320×320 may be employed. Due to, for example, computational time restrictions, utilization of a large DFOV but a small reconstruction size may be impractical to achieve. Due to the limited spatial resolution in conventional first-pass initial image reconstruction, artifacts may appear in MMC corrected images. For example, jagged artifacts, which may appear in the presence of metal, may appear. As another example, undershoots, which may appear near sharp boundaries (e.g., a bone/brain interface), may also appear.